Bayesian Modeling of Spatiotemporal patterns of TB-HIV co-infection risk in Kenya

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Abstract Background Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) diseases are globally acknowledged as public health challenges exhibiting adverse bidirectional relations due to the co-epidemic overlap. To understand the co-infection burden we used case notification data to generate spatiotemporal maps to describe risk patterns for further epidemiologic investigations. These model maps are relevant for geographically targeting interventions towards suppressing co-infectionMethods We analyzed the TB and TB-HIV case notification data from the Kenya national TB control program aggregated for forty-seven counties over a seven-year period (2012 – 2018). Using the Integrated Nested Laplace Approach (INLA), we modeled the risk of TB-HIV co-infection. Six competing models with varying space-time formulations were compared to determine the best fit model. We assessed the space-time patterns of coinfection risk by mapping the posterior marginal from the best fit model.Results Of the total 608312 TB case notifications, 194129 were HIV co-infected. The proportion of TB-HIV co-infection was higher in female (39.7%) than to male (27.0%). A significant share of the co-infection was among adults aged 35 to 44 years (46.7%) and 45 to 54 years (42.1%). Based on the Bayesian Defiance Information (DIC) and the effective number of parameters comparisons, the spatiotemporal model 3b was the best in explaining the geographical variations in TB-HIV coinfection. The model results suggested that the risk of TB-HIV coinfection was influenced by infrastructure index (5.75, Credible Interval (Cr.I) = (1.65, 19.89) and gender ratio (5.81e-04, Cr.I = (1.06e-04, 3.18e-03)). The lowest and highest temporal risks were in the years 2016 at 0.9 and 2012 at 1.07 respectively. The spatial pattern presented increased co-infection risk in various counties. For the spatiotemporal interaction, few counties had a probability of risk greater than 1 that varied in different years.Conclusions TB-HIV co-epidemic in Kenya is at a critical point portending a dual endemic challenge for many years to come. Integration of care for both TB and HIV using a single facility and single health provider in each county will enable proper monitoring of the co-infection trends and subsequently significant reduction of HIV burden amongst TB patients and TB burden amongst HIV patients

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